As of June 2022, more than *** hours of video were uploaded to YouTube every minute. This equates to approximately ****** hours of newly uploaded content per hour. The amount of content on YouTube has increased dramatically as consumer’s appetites for online video has grown. In fact, the number of video content hours uploaded every 60 seconds grew by around ** percent between 2014 and 2020. YouTube global users Online video is one of the most popular digital activities worldwide, with ** percent of internet users worldwide watching more than ** hours of online videos on a weekly basis in 2023. It was estimated that in 2023 YouTube would reach approximately *** million users worldwide. In 2022, the video platform was one of the leading media and entertainment brands worldwide, with a value of more than ** billion U.S. dollars. YouTube video content consumption The most viewed YouTube channels of all time have racked up billions of viewers, millions of subscribers and cover a wide variety of topics ranging from music to cosmetics. The YouTube channel owner with the most video views is Indian music label T-Series, which counted ****** billion lifetime views. Other popular YouTubers are gaming personalities such as PewDiePie, DanTDM and Markiplier.

This is the statistics for the Top 10 songs of various spotify artists and their YouTube videos. The Creators above generated the data and uploaded it to Kaggle on February 6-7 2023. The license to use this data is "CC0: Public Domain", allowing the data to be copied, modified, distributed, and worked on without having to ask permission. The data is in numerical and textual CSV format as attached. This dataset contains the statistics and attributes of the top 10 songs of various artists in the world. As described by the creators above, it includes 26 variables for each of the songs collected from spotify. These variables are briefly described next:

Track: name of the song, as visible on the Spotify platform. Artist: name of the artist. Url_spotify: the Url of the artist. Album: the album in wich the song is contained on Spotify. Album_type: indicates if the song is relesead on Spotify as a single or contained in an album. Uri: a spotify link used to find the song through the API. Danceability: describes how suitable a track is for dancing based on a combination of musical elements including tempo, rhythm stability, beat strength, and overall regularity. A value of 0.0 is least danceable and 1.0 is most danceable. Energy: is a measure from 0.0 to 1.0 and represents a perceptual measure of intensity and activity. Typically, energetic tracks feel fast, loud, and noisy. For example, death metal has high energy, while a Bach prelude scores low on the scale. Perceptual features contributing to this attribute include dynamic range, perceived loudness, timbre, onset rate, and general entropy. Key: the key the track is in. Integers map to pitches using standard Pitch Class notation. E.g. 0 = C, 1 = C♯/D♭, 2 = D, and so on. If no key was detected, the value is -1. Loudness: the overall loudness of a track in decibels (dB). Loudness values are averaged across the entire track and are useful for comparing relative loudness of tracks. Loudness is the quality of a sound that is the primary psychological correlate of physical strength (amplitude). Values typically range between -60 and 0 db. Speechiness: detects the presence of spoken words in a track. The more exclusively speech-like the recording (e.g. talk show, audio book, poetry), the closer to 1.0 the attribute value. Values above 0.66 describe tracks that are probably made entirely of spoken words. Values between 0.33 and 0.66 describe tracks that may contain both music and speech, either in sections or layered, including such cases as rap music. Values below 0.33 most likely represent music and other non-speech-like tracks. Acousticness: a confidence measure from 0.0 to 1.0 of whether the track is acoustic. 1.0 represents high confidence the track is acoustic. Instrumentalness: predicts whether a track contains no vocals. "Ooh" and "aah" sounds are treated as instrumental in this context. Rap or spoken word tracks are clearly "vocal". The closer the instrumentalness value is to 1.0, the greater likelihood the track contains no vocal content. Values above 0.5 are intended to represent instrumental tracks, but confidence is higher as the value approaches 1.0. Liveness: detects the presence of an audience in the recording. Higher liveness values represent an increased probability that the track was performed live. A value above 0.8 provides strong likelihood that the track is live. Valence: a measure from 0.0 to 1.0 describing the musical positiveness conveyed by a track. Tracks with high valence sound more positive (e.g. happy, cheerful, euphoric), while tracks with low valence sound more negative (e.g. sad, depressed, angry). Tempo: the overall estimated tempo of a track in beats per minute (BPM). In musical terminology, tempo is the speed or pace of a given piece and derives directly from the average beat duration. Duration_ms: the duration of the track in milliseconds. Stream: number of streams of the song on Spotify. Url_youtube: url of the video linked to the song on Youtube, if it have any. Title: title of the videoclip on youtube. Channel: name of the channel that have published the video. Views: number of views. Likes: number of likes. Comments: number of comments. Description: description of the video on Youtube. Licensed: Indicates whether the video represents licensed content, which means that the content was uploaded to a channel linked to a YouTube content partner and then claimed by that partner. official_video: boolean value that indicates if the video found is the official video of the song. The data was last updated on February 7, 2023.

Use our YouTube profiles dataset to extract both business and non-business information from public channels and filter by channel name, views, creation date, or subscribers. Datapoints include URL, handle, banner image, profile image, name, subscribers, description, video count, create date, views, details, and more. You may purchase the entire dataset or a customized subset, depending on your needs. Popular use cases for this dataset include sentiment analysis, brand monitoring, influencer marketing, and more.

As of February 2025, India was the country with the largest YouTube audience by far, with approximately 491 million users engaging with the popular social video platform. The United States followed, with around 253 million YouTube viewers. Brazil came in third, with 144 million users watching content on YouTube. The United Kingdom saw around 54.8 million internet users engaging with the platform in the examined period. What country has the highest percentage of YouTube users? In July 2024, the United Arab Emirates was the country with the highest YouTube penetration worldwide, as around 94 percent of the country's digital population engaged with the service. In 2024, YouTube counted around 100 million paid subscribers for its YouTube Music and YouTube Premium services. YouTube mobile markets In 2024, YouTube was among the most popular social media platforms worldwide. In terms of revenues, the YouTube app generated approximately 28 million U.S. dollars in revenues in the United States in January 2024, as well as 19 million U.S. dollars in Japan.

Recent accelerations in multi-modal applications have been made possible with the plethora of image and text data available online. However, the scarcity of similar data in the medical field, specifically in histopathology, has slowed similar progress. To enable similar representation learning for histopathology, we turn to YouTube, an untapped resource of videos, offering 1,087 hours of valuable educational histopathology videos from expert clinicians. From YouTube, we curate Quilt: a large-scale vision-language dataset consisting of 802,148 image and text pairs. Quilt was automatically curated using a mixture of models, including large language models), handcrafted algorithms, human knowledge databases, and automatic speech recognition. In comparison, the most comprehensive datasets curated for histopathology amass only around 200K samples. We combine Quilt with datasets, from other sources, including Twitter, research papers, and the internet in general, to create an even larger dataset: Quilt-1M, with 1M paired image-text samples, marking it as the largest vision-language histopathology dataset to date. We demonstrate the value of Quilt-1M by fine-tuning a pre-trained CLIP model. Our model outperforms state-of-the-art models on both zero-shot and linear probing tasks for classifying new pathology images across 13 diverse patch-level datasets of 8 different sub-pathologies and cross-modal retrieval tasks.

We propose a large-scale multimodal video log database (LMVD) for identifying depression in the wild. In LMVD, there were 1823 samples, capturing 214 hours of 1475 participants from four multimedia platforms (Sina Weibo, Bilibili, Tiktok, and YouTube). For all collected data, we extract video features and audio features separately. For audio features, use a pre trained VGGish41 model. For visual features, use FAU, facial markers, eye gaze, and head posture features. It is worth mentioning that our LMVD is the largest dataset for identifying visual and auditory depression in an individual's daily life, which is a positive contribution to the field of emotional computing.

Context

This is the dataset required for Keith Galli's 'Solving real world data science tasks with Python Pandas!' video. Where he analyzes and answers business questions for 12 months worth of business data. The data contains hundreds of thousands of electronics store purchases broken down by month, product type, cost, purchase address, etc.

I decided to upload the data here so that I can carry out the exercise straight on Kaggle Notebooks. Making it ready for viewing as a portfolio project.

Content

12 .csv files containing sales data for each month of 2019.

Acknowledgements

Of course, all thanks goes to Keith Galli and the great work he does with his tutorials. He has several other amazing tutorials that you can follow and subscribe at his channel.

This dataset provides estimated YouTube RPM (Revenue Per Mille) ranges for different niches in 2025, based on ad revenue earned per 1,000 monetized views.

I have created this dataset to showcase the use of predictive modeling using the stock market as a case study. This dataset is designed to help and predict tomorrow's Amazon stock price. If you want to get the most updated dataset you will need to pull them in real time. I have shared my code to pull data using Yahoo Finance API and preprocess it in Data Analytics for Fun Github Repository

The uploaded dataset is for Jan 11, 2021.

What are the columns?

yes_changeP: Yesterday Amazon's stock price change lastweek_changeP: Last week Amazon's stock price change dow_yes_changeP: Yesterday Dow Jones change dow_lastweek_changeP: Last Week Dow Jones change nasdaq_yes_changeP: Yesterday NASDAQ 100 change nasdaq_lastweek_changeP: Last Week NASDAQ 100 change today_changeP: Today Amazon's stock price change

To learn more about the dataset and see a very simple prediction model applied to the dataset you may watch this YouTube Video where I have explained the dataset and also prediction: A Taste for Prediction: Predict Tomorrow's Amazon Stock Price

In 2021, YouTube's user base in Nigeria amounts to approximately **** million users. The number of YouTube users in Nigeria is projected to reach ***** million users by 2025. User figures have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

How much time do people spend on social media?

              As of 2024, the average daily social media usage of internet users worldwide amounted to 143 minutes per day, down from 151 minutes in the previous year. Currently, the country with the most time spent on social media per day is Brazil, with online users spending an average of three hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in
              the U.S. was just two hours and 16 minutes. Global social media usageCurrently, the global social network penetration rate is 62.3 percent. Northern Europe had an 81.7 percent social media penetration rate, topping the ranking of global social media usage by region. Eastern and Middle Africa closed the ranking with 10.1 and 9.6 percent usage reach, respectively.
              People access social media for a variety of reasons. Users like to find funny or entertaining content and enjoy sharing photos and videos with friends, but mainly use social media to stay in touch with current events friends. Global impact of social mediaSocial media has a wide-reaching and significant impact on not only online activities but also offline behavior and life in general.
              During a global online user survey in February 2019, a significant share of respondents stated that social media had increased their access to information, ease of communication, and freedom of expression. On the flip side, respondents also felt that social media had worsened their personal privacy, increased a polarization in politics and heightened everyday distractions.

The live video analytics market is experiencing robust growth, driven by the increasing adoption of live streaming across various sectors. The surge in popularity of live video content on platforms like YouTube, Twitch, and Facebook, coupled with the need for businesses to understand audience engagement and optimize their content strategies, is fueling market expansion. The market's compound annual growth rate (CAGR) is estimated at 15% between 2025 and 2033, indicating a significant opportunity for technology providers and businesses alike. Key drivers include the rising demand for enhanced viewer experience, improved content monetization strategies, and the need for real-time data-driven decision-making. Advancements in artificial intelligence (AI) and machine learning (ML) are further accelerating market growth, enabling more sophisticated analytics and predictive capabilities. The market is segmented by deployment type (cloud, on-premise), application (media & entertainment, education, e-commerce, enterprise communications), and geographic region. While the cloud deployment model holds a significant market share due to its scalability and cost-effectiveness, on-premise deployments are still prevalent in certain sectors prioritizing data security and control. Major players in the market, including Adobe, Akamai, Brightcove, and Vimeo, are continuously innovating to meet the evolving needs of businesses. Their offerings encompass comprehensive analytics dashboards, real-time monitoring tools, and predictive analytics capabilities. However, challenges remain, including data privacy concerns, high implementation costs associated with certain advanced solutions, and the need for robust data infrastructure to support large-scale live video analytics. Despite these restraints, the market is poised for continued expansion as businesses increasingly recognize the value of leveraging data-driven insights to optimize their live video strategies and enhance viewer engagement. The forecast period of 2025-2033 projects significant growth in all major segments, fueled by technological advancements and expanding applications across various industries.

Snapshot img

Visual Content Market Size 2025-2029

The visual content market size is forecast to increase by USD 1.24 billion at a CAGR of 5.1% between 2024 and 2029.

The market, encompassing digital stock images and software-generated graphics, continues to experience significant growth In the US. Key drivers include the increasing demand for digital content in various sectors such as real estate, education, and digital marketing. A catalyst for this growth is the rising preference for visuals like 360-degree images and videos. However, the market faces challenges, including limited online video consumption due to slow internet speeds. As digital marketing becomes more prevalent, the need for high-quality, visually engaging content is increasingly important. This trend is expected to continue, with advancements in technology further enhancing the potential of visual content to captivate audiences and drive engagement.

What will be the Size of the Visual Content Market During the Forecast Period?

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The market continues to expand as businesses recognize the power of engaging, shareable content to capture audience attention and drive performance. The human brain processes visual information 60,000 times faster than text, making infographics, videos, photos, and interactive visuals effective tools for conveying complex information and boosting brand awareness. For example, a brand may include a CTA in an infographic, inviting users to sign up for a newsletter or download an e-book. Visual content drives ROI through increased traffic, backlinks, and calls to action. 



Platforms and others provide businesses with a range of image-based and interactive content solutions. As the market evolves, expect to see a continued focus on creating high-quality, shareable visuals that resonate with audiences and deliver measurable results. Visual capitalists are leveraging a variety of formats, including pictures, diagrams, charts, online videos, slide decks, native video, and ultimate guides, to present complex data and insights in an engaging and accessible way.

How is this Visual Content Industry segmented and which is the largest segment?

The industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Product

  Stock images
  Stock video


Application

  Editorial
  Commercial


License Model

  RF
  RM


End-user

  Media and entertainment
  Advertising
  Corporate
  Others


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK
    France
    Italy


  APAC

    China
    India
    Japan


  Middle East and Africa



  South America

By Product Insights

The stock images segment is estimated to witness significant growth during the forecast period.

The market experienced significant growth in 2024, with stock images leading the segment. The proliferation of digital photography, driven by the easy accessibility and affordability of digital single-lens reflex (DSLR) cameras, has contributed to market expansion. Notably, there has been an increasing trend of collaborations among companies, enabling them to broaden their offerings, reach larger audiences, and enhance customer value. The market exhibits minimal price differentiation based on picture resolution due to the transition to mobile and online platforms. The demand for responsive web design has fueled the need for high-quality, small images, leading to advancements in image resolution technology. Visual content encompasses various formats, including infographics, videos, YouTube, Hubspot, and social media, among others.

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The stock images segment was valued at USD 3.38 billion in 2019 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 38% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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The North American market holds the largest share In the global visual content industry. The US is the primary contributor to this market's growth due to the increasing demand for video content among commercial consumers. Factors such as enhanced broadband penetration and faster internet speeds facilitate smoother video consumption. Furthermore, the proliferation of social media platforms like Facebook and Instagram In the US fuels market expansion. Visual content encompasses various formats, including infographics, videos, YouTube, Hubspot, and interactive visuals. These ele

A curated dataset of over 400 unique and creative YouTube channel name ideas organized by popular niches such as gaming, travel, tech, beauty, vlogging, pets, DIY, education, and more. Includes a free YouTube channel name generator to help creators find inspiration for their brand.

As of April 2024, almost 32 percent of global Instagram audiences were aged between 18 and 24 years, and 30.6 percent of users were aged between 25 and 34 years. Overall, 16 percent of users belonged to the 35 to 44 year age group.

              Instagram users

              With roughly one billion monthly active users, Instagram belongs to the most popular social networks worldwide. The social photo sharing app is especially popular in India and in the United States, which have respectively 362.9 million and 169.7 million Instagram users each.

              Instagram features

              One of the most popular features of Instagram is Stories. Users can post photos and videos to their Stories stream and the content is live for others to view for 24 hours before it disappears. In January 2019, the company reported that there were 500 million daily active Instagram Stories users. Instagram Stories directly competes with Snapchat, another photo sharing app that initially became famous due to it’s “vanishing photos” feature.
              As of the second quarter of 2021, Snapchat had 293 million daily active users.

In 2021, there were 1.21 billion monthly active users of Meta's Instagram, making up over 28 percent of the world's internet users. By 2025, it has been forecast that there will be 1.44 billion monthly active users of the social media platform, which would account for 31.2 percent of global internet users.

How popular is Instagram?

Instagram, as of January 2022, was the fourth most popular social media platform in the world in terms of user numbers. YouTube and WhatsApp ranked in second and third place, respectively, whilst Facebook remained the most popular, with almost three billion monthly active users worldwide.

India had the largest number of Instagram users as of January 2022, with a total of over 230 million users in the country. The second-largest Instagram audience could be found in the United States, with almost 160 million people subscribing to the photo and video sharing app.

Gen Z and Instagram

As of September 2021, Gen Z users in the United States spent an average of five hours per week on Instagram. Although Instagram ranked third in terms of hours per week spent on the platform, Gen Z users spent considerably more time on TikTok, amounting to a weekly average of over 10 hours being spent on the mobile-first video app.

Most followed accounts on Instagram

As of May 2022, Instagram’s own account had 504.37 million followers. In terms of celebrities, Portuguese footballer Cristiano Ronaldo (@chistiano) had over 440.41 million followers on the social network. Moreover, the average media value of an Instagram post by Ronaldo was over 985,000 U.S. dollars.

The most liked post on Instagram as of May 2022 was Photo of an Egg, which was posted in 2019 by the account @world_record_egg. Photo of an Egg has not only exceeded 55 million likes on the platform, but it also has nearly 3.5 million comments, and the account itself has over 4.5 million Instagram followers. After mysterious posts published by the account, World Record Egg revealed itself as part of a mental health campaign aimed at the difficulties and demands of using social media.